SussexDigital
AI Engineer – 2027 (UK – Burgess Hill)
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American Express
Burgess Hill
American Express is recruiting for the role of Campus – Full Time – AI Engineer – 2027 (UK – Burgess Hill). An AI Engineer I in Enterprise Technology Services will help teams explore, build, test and responsibly scale AI-enabled solutions. The role supports work across machine learning, generative AI, intelligent automation, data pipelines and AI agents, while collaborating with technical and business partners.
Role details
- Location: Burgess Hill
- Working pattern: Hybrid
- Job type: Full time
- Closing date: 23/10/2026
What you’ll do
- Support the development, testing and integration of AI and ML models, LLM integrations, intelligent services or data retrieval pipelines under guidance.
- Assist with data collection, preprocessing, transformation and validation for model training, testing, evaluation and implementation.
- Help debug and improve AI-enabled solutions to strengthen performance, reliability, explainability, maintainability and quality.
- Support AI capabilities including training workflows, inference endpoints, prompt-based interactions, evaluation routines, retrieval patterns, AI agents or agentic workflows.
- Collaborate with engineering, product, data, risk, security and business partners to implement AI-driven solutions aligned to business requirements.
- Document model parameters, prompts, assumptions, data pipelines, integrations and technical decisions to support reproducibility and knowledge sharing.
- Participate in Agile practices including sprint planning, stand-ups, demos, retrospectives, code reviews and team ceremonies.
- Help ensure AI systems and AI-enabled features align with expectations for reliability, safety, governance, security, compliance and escalation.
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What they’re looking for
- Have a Bachelor’s or Master’s degree in a technical field before the full-time start date.
- Have a graduation date between December 2026 and June 2027.
- Know Python and foundational data processing technologies.
- Understand core computer science concepts, including data structures, algorithms, object-oriented programming, debugging, testing and problem solving.
- Understand basic machine learning concepts such as supervised learning, unsupervised learning, model training, evaluation, feature engineering and experimentation.
- Understand modern AI systems, including LLM APIs, prompt-based interactions, retrieval patterns, AI powered tools or generative AI applications.
- Be able to support AI and ML development, testing, documentation, integration or data pipeline activities under guidance.
- Bring strong communication, collaboration, documentation and learning agility across technical and non-technical teams.
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Additional role information
- Experience from coursework, research, projects, open-source contributions, internships, hackathons or extracurricular activities is preferred.
- Interest in machine learning, generative AI, natural language processing, intelligent automation, data engineering, agentic AI or AI-enabled software development is preferred.
- There is exposure to Git, CI/CD, version control, testing, code reviews, Agile development and collaborative software engineering workflows.
- Familiarity is mentioned with APIs, data pipelines, ETL processes, cloud environments, containerized development, model deployment patterns or monitoring.
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